- using R version 2.15.0 Patched (2012-04-12 r58988)
- using platform: sparc-sun-solaris2.10 (32-bit)
- using session charset: UTF-8
- checking for file ‘censReg/DESCRIPTION’ ... OK
- this is package ‘censReg’ version ‘0.5-10’
- checking package namespace information ... OK
- checking package dependencies ... OK
- checking if this is a source package ... OK
- checking if there is a namespace ... OK
- checking for .dll and .exe files ... OK
- checking whether package ‘censReg’ can be installed ... OK
- checking installed package size ... OK
- checking package directory ... OK
- checking for portable file names ... OK
- checking for sufficient/correct file permissions ... OK
- checking DESCRIPTION meta-information ... OK
- checking top-level files ... OK
- checking index information ... OK
- checking package subdirectories ... OK
- checking R files for non-ASCII characters ... OK
- checking R files for syntax errors ... OK
- checking whether the package can be loaded ... OK
- checking whether the package can be loaded with stated dependencies ... OK
- checking whether the package can be unloaded cleanly ... OK
- checking whether the namespace can be loaded with stated dependencies ... OK
- checking whether the namespace can be unloaded cleanly ... OK
- checking for unstated dependencies in R code ... OK
- checking S3 generic/method consistency ... OK
- checking replacement functions ... OK
- checking foreign function calls ... OK
- checking R code for possible problems ... NOTE
censReg: no visible binding for global variable ‘validObs2’
- checking Rd files ... OK
- checking Rd metadata ... OK
- checking Rd cross-references ... OK
- checking for missing documentation entries ... OK
- checking for code/documentation mismatches ... OK
- checking Rd \usage sections ... OK
- checking Rd contents ... OK
- checking for unstated dependencies in examples ... OK
- checking installed files from ‘inst/doc’ ... OK
- checking examples ... [40s/40s] OK
- checking for unstated dependencies in tests ... OK
- checking tests ... [13m/13m] OK
Running ‘censRegPanelLargerTest.R’ [38s/38s]
Comparing ‘censRegPanelLargerTest.Rout’ to ‘censRegPanelLargerTest.Rout.save’ ... OK
Running ‘censRegPanelTest.R’ [539s/539s]
Comparing ‘censRegPanelTest.Rout’ to ‘censRegPanelTest.Rout.save’ ...68c68
< logSigmaMu -0.129547 0.258070 -0.5020 0.6156792
---
> logSigmaMu -0.129547 0.258070 -0.5020 0.6156793
127c127
< (Intercept) 0.225109672 -0.020570168 -0.254602886 -0.023824162 -0.002973952
---
> (Intercept) 0.225109671 -0.020570168 -0.254602886 -0.023824162 -0.002973952
129c129
< x2 -0.254602886 0.008562225 0.454125882 0.017179542 0.001505438
---
> x2 -0.254602886 0.008562225 0.454125881 0.017179542 0.001505438
134,137c134,137
< (Intercept) 0.225109672 -0.020570168 -0.254602886 -0.020929366 -0.002937279
< x1 -0.020570168 0.043773972 0.008562225 0.011775393 0.002933333
< x2 -0.254602886 0.008562225 0.454125882 0.015092113 0.001486874
< sigmaMu -0.020929366 0.011775393 0.015092113 0.051398826 -0.002289643
---
> (Intercept) 0.225109671 -0.020570168 -0.254602886 -0.020929366 -0.002937279
> x1 -0.020570168 0.043773972 0.008562225 0.011775394 0.002933333
> x2 -0.254602886 0.008562225 0.454125881 0.015092113 0.001486874
> sigmaMu -0.020929366 0.011775394 0.015092113 0.051398826 -0.002289643
143,144c143,144
< x2 2.24054376 0.6738886 3.32479829 8.848252e-04
< logSigmaMu -0.12954703 0.2580704 -0.50198333 6.156792e-01
---
> x2 2.24054376 0.6738886 3.32479830 8.848252e-04
> logSigmaMu -0.12954703 0.2580704 -0.50198333 6.156793e-01
170c170
< 1.712581e-11 4.533016e-11 1.345443e-11 8.220230e-12 6.210468e-11
---
> 1.711386e-11 4.533762e-11 1.344722e-11 8.216400e-12 6.207498e-11
604c604
< -0.37023 1.68022 2.24759 -0.12912 -0.01236
---
> -0.36750 1.67993 2.24379 -0.12947 -0.01241
611c611
< Log-Likelihood: -73.19888
---
> Log-Likelihood: -73.19883
615,619c615,619
< (Intercept) -0.370232 0.474949 -0.7795 0.4356739
< x1 1.680221 0.209277 8.0287 9.851e-16 ***
< x2 2.247590 0.674143 3.3340 0.0008561 ***
< logSigmaMu -0.129120 0.257991 -0.5005 0.6167339
< logSigmaNu -0.012365 0.129702 -0.0953 0.9240501
---
> (Intercept) -0.367502 0.474613 -0.7743 0.4387426
> x1 1.679929 0.209229 8.0291 9.816e-16 ***
> x2 2.243794 0.673969 3.3292 0.0008709 ***
> logSigmaMu -0.129473 0.258047 -0.5017 0.6158482
> logSigmaNu -0.012409 0.129690 -0.0957 0.9237740
634,638c634,638
< (Intercept) -0.37023 0.47495 -0.780 0.435674
< x1 1.68022 0.20928 8.029 9.85e-16 ***
< x2 2.24759 0.67414 3.334 0.000856 ***
< logSigmaMu -0.12912 0.25799 -0.500 0.616734
< logSigmaNu -0.01236 0.12970 -0.095 0.924050
---
> (Intercept) -0.36750 0.47461 -0.774 0.438743
> x1 1.67993 0.20923 8.029 9.82e-16 ***
> x2 2.24379 0.67397 3.329 0.000871 ***
> logSigmaMu -0.12947 0.25805 -0.502 0.615848
> logSigmaNu -0.01241 0.12969 -0.096 0.923774
644c644
< Log-likelihood: -73.19888 on 5 Df
---
> Log-likelihood: -73.19883 on 5 Df
648c648
< [1] -73.19888
---
> [1] -73.19883
652c652
< -0.37023230 1.68022057 2.24759034 -0.12912036 -0.01236491
---
> -0.36750163 1.67992931 2.24379444 -0.12947348 -0.01240886
656c656
< 0.0080480603 0.0013305834 -0.0109845702 -0.0009545502 -0.0004683449
---
> 0.0014212306 0.0034992596 -0.0064419525 0.0003782988 0.0003341343
660,664c660,664
< (Intercept) -13.306993 -4.094966 -7.3016122 -2.1350119 -1.2902336
< x1 -4.094966 -26.068270 -1.9885298 4.4813349 4.7590560
< x2 -7.301612 -1.988530 -6.2332040 -0.6336632 -0.4464176
< logSigmaMu -2.135012 4.481335 -0.6336632 -16.6813720 -3.7185288
< logSigmaNu -1.290234 4.759056 -0.4464176 -3.7185288 -61.0536175
---
> (Intercept) -13.317517 -4.096146 -7.3057987 -2.1155739 -1.300861
> x1 -4.096146 -26.075639 -1.9898094 4.4840349 4.755412
> x2 -7.305799 -1.989809 -6.2353998 -0.6259168 -0.464233
> logSigmaMu -2.115574 4.484035 -0.6259168 -16.6651955 -3.721179
> logSigmaNu -1.300861 4.755412 -0.4642330 -3.7211788 -61.065093
687,701c687,701
< [1,] -0.85199137 0.22379118 -0.07345967 -0.1446569 -0.9676550
< [2,] -1.70281635 0.04674831 -1.19066184 1.6820349 -1.0125029
< [3,] 1.74991751 0.33326384 1.72490952 1.8352014 1.7951045
< [4,] 0.15548576 -0.20323447 -0.43364056 -0.6890178 -1.4278996
< [5,] 0.12989065 0.98291215 0.68740126 -0.6768874 -0.5617200
< [6,] 0.33011912 -0.30573161 0.38378812 -0.4918887 -1.5822020
< [7,] -0.07979653 -3.18602171 -0.23679061 -0.6772242 6.0320587
< [8,] -0.26554601 0.37782492 0.05576143 -0.5390741 -1.1085099
< [9,] 1.14876154 0.59374960 0.30323926 0.1347705 -1.6153056
< [10,] -0.43355401 -0.40484513 -0.15201143 -0.4698409 -1.9368856
< [11,] -0.02771595 1.45035959 -0.64470552 -0.9184525 2.7423588
< [12,] 1.20985117 0.53838077 0.61106296 0.2048135 -1.7333264
< [13,] 0.53665128 -0.22536070 0.33121654 -0.3682552 -1.4085157
< [14,] -1.81419999 -1.30762331 -0.91981070 1.9582763 2.5771097
< [15,] -0.07700874 1.08711714 -0.45728334 -0.8407535 0.2074227
---
> [1,] -0.85278081 0.2247850 -0.07302970 -0.1442070 -0.9634923
> [2,] -1.70342425 0.0476419 -1.19055345 1.6820162 -1.0127268
> [3,] 1.75059965 0.3340379 1.72645582 1.8351650 1.8000202
> [4,] 0.15552297 -0.2026892 -0.43296702 -0.6893599 -1.4315786
> [5,] 0.12953233 0.9838683 0.68846571 -0.6770129 -0.5576955
> [6,] 0.33020957 -0.3070305 0.38415893 -0.4921914 -1.5806796
> [7,] -0.08124385 -3.1854369 -0.23706941 -0.6768114 6.0284476
> [8,] -0.26650783 0.3785437 0.05560267 -0.5386742 -1.1090288
> [9,] 1.14849813 0.5942606 0.30325840 0.1336487 -1.6163416
> [10,] -0.43466534 -0.4056715 -0.15242875 -0.4690608 -1.9368240
> [11,] -0.02815366 1.4492071 -0.64446998 -0.9176305 2.7387662
> [12,] 1.21036511 0.5376472 0.61231215 0.2052291 -1.7342086
> [13,] 0.53592238 -0.2250517 0.33100094 -0.3690601 -1.4085335
> [14,] -1.81473915 -1.3068211 -0.91982779 1.9580283 2.5799493
> [15,] -0.07771403 1.0862084 -0.45735047 -0.8397008 0.2042601
804c804
< 4.63363 1.68002 2.24180 -0.12949 -0.01249
---
> 4.62970 1.67974 2.24826 -0.12967 -0.01247
809,813c809,811
< BFGSR maximization, 100 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
< Log-Likelihood: -73.19882
---
> BFGSR maximization, 75 iterations
> Return code 2: successive function values within tolerance limit
> Log-Likelihood: -73.19889
817,821c815,819
< (Intercept) 4.633634 0.474516 9.7650 < 2.2e-16 ***
< x1 1.680023 0.209215 8.0301 9.737e-16 ***
< x2 2.241803 0.673880 3.3267 0.0008788 ***
< logSigmaMu -0.129488 0.258035 -0.5018 0.6157922
< logSigmaNu -0.012488 0.129680 -0.0963 0.9232824
---
> (Intercept) 4.629702 0.474777 9.7513 < 2.2e-16 ***
> x1 1.679738 0.209226 8.0284 9.878e-16 ***
> x2 2.248262 0.674033 3.3355 0.0008513 ***
> logSigmaMu -0.129673 0.258097 -0.5024 0.6153734
> logSigmaNu -0.012466 0.129691 -0.0961 0.9234264
836,840c834,838
< (Intercept) 4.63363 0.47452 9.765 < 2e-16 ***
< x1 1.68002 0.20921 8.030 9.74e-16 ***
< x2 2.24180 0.67388 3.327 0.000879 ***
< logSigmaMu -0.12949 0.25803 -0.502 0.615792
< logSigmaNu -0.01249 0.12968 -0.096 0.923282
---
> (Intercept) 4.62970 0.47478 9.751 < 2e-16 ***
> x1 1.67974 0.20923 8.028 9.88e-16 ***
> x2 2.24826 0.67403 3.336 0.000851 ***
> logSigmaMu -0.12967 0.25810 -0.502 0.615373
> logSigmaNu -0.01247 0.12969 -0.096 0.923426
844,848c842,844
< BFGSR maximization, 100 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
< Log-likelihood: -73.19882 on 5 Df
---
> BFGSR maximization, 75 iterations
> Return code 2: successive function values within tolerance limit
> Log-likelihood: -73.19889 on 5 Df
852c848
< 4.63363402 1.68002313 2.24180291 -0.12948769 -0.01248821
---
> 4.62970160 1.67973837 2.24826176 -0.12967269 -0.01246575
855c851
< 4.6336340 1.6800231 2.2418029 0.8785454 0.9875894
---
> 4.6297016 1.6797384 2.2482618 0.8783829 0.9876116
858,862c854,858
< (Intercept) 0.225165667 -0.020585730 -0.254631964 -0.023855252 -0.002986321
< x1 -0.020585730 0.043770852 0.008580805 0.013404055 0.002969232
< x2 -0.254631964 0.008580805 0.454114349 0.017198112 0.001539042
< logSigmaMu -0.023855252 0.013404055 0.017198112 0.066581904 -0.002635515
< logSigmaNu -0.002986321 0.002969232 0.001539042 -0.002635515 0.016816996
---
> (Intercept) 0.225413235 -0.020660460 -0.254872111 -0.024058747 -0.003055367
> x1 -0.020660460 0.043775353 0.008670292 0.013424948 0.002954403
> x2 -0.254872111 0.008670292 0.454320177 0.017344565 0.001704899
> logSigmaMu -0.024058747 0.013424948 0.017344565 0.066614118 -0.002644224
> logSigmaNu -0.003055367 0.002954403 0.001704899 -0.002644224 0.016819840
865,869c861,865
< (Intercept) 0.225165667 -0.020585730 -0.254631964 -0.020957922 -0.002949259
< x1 -0.020585730 0.043770852 0.008580805 0.011776071 0.002932382
< x2 -0.254631964 0.008580805 0.454114349 0.015109322 0.001519942
< sigmaMu -0.020957922 0.011776071 0.015109322 0.051390712 -0.002286684
< sigmaNu -0.002949259 0.002932382 0.001519942 -0.002286684 0.016402169
---
> (Intercept) 0.225413235 -0.020660460 -0.254872111 -0.021132792 -0.003017516
> x1 -0.020660460 0.043775353 0.008670292 0.011792244 0.002917803
> x2 -0.254872111 0.008670292 0.454320177 0.015235169 0.001683778
> sigmaMu -0.021132792 0.011792244 0.015235169 0.051396556 -0.002293867
> sigmaNu -0.003017516 0.002917803 0.001683778 -0.002293867 0.016405681
871c867
< 'log Lik.' -73.19882 (df=5)
---
> 'log Lik.' -73.19889 (df=5)
873c869
< [1] -40.0000 156.3976
---
> [1] -40.0000 156.3978
876c872
< [1] -73.19882
---
> [1] -73.19889
880c876
< 4.63363402 1.68002313 2.24180291 -0.12948769 -0.01248821
---
> 4.62970160 1.67973837 2.24826176 -0.12967269 -0.01246575
884c880
< 5.956686e-04 -7.749401e-05 -2.461182e-03 1.764174e-04 5.133549e-03
---
> 0.007307875 0.009883823 -0.013334396 0.006186400 0.005241257
888,892c884,888
< (Intercept) -13.320003 -4.096850 -7.3070098 -2.1118076 -1.3042287
< x1 -4.096850 -26.079326 -1.9904015 4.4849891 4.7621248
< x2 -7.307010 -1.990401 -6.2364004 -0.6251604 -0.4733692
< logSigmaMu -2.111808 4.484989 -0.6251604 -16.6644476 -3.7212812
< logSigmaNu -1.304229 4.762125 -0.4733692 -3.7212812 -61.0759302
---
> (Intercept) -13.320457 -4.097602 -7.3082204 -2.1336126 -1.2945958
> x1 -4.097602 -26.078345 -1.9899709 4.4821291 4.7426563
> x2 -7.308220 -1.989971 -6.2371991 -0.6321033 -0.4451737
> logSigmaMu -2.133613 4.482129 -0.6321033 -16.6692492 -3.7313402
> logSigmaNu -1.294596 4.742656 -0.4451737 -3.7313402 -61.0632866
895c891
< [1] 3
---
> [1] 2
898c894
< [1] "Last step could not find a value above the current.\nBoundary of parameter space? \nConsider switching to a more robust optimisation method temporarily."
---
> [1] "successive function values within tolerance limit"
901,903c897
< $last.step$theta0
< (Intercept) x1 x2 logSigmaMu logSigmaNu
< 4.6336312 1.6800028 2.2417860 -0.1294694 -0.0123293
---
> NULL
905,928d898
< $last.step$f0
< [1] -73.19882
< attr(,"gradient")
< [,1] [,2] [,3] [,4] [,5]
< [1,] -0.85285116 0.22520391 -0.07277818 -0.1441324 -0.9622137
< [2,] -1.70306444 0.04811529 -1.19001042 1.6810528 -1.0131173
< [3,] 1.75047981 0.33380319 1.72688570 1.8348800 1.8021747
< [4,] 0.15571531 -0.20249726 -0.43241948 -0.6891767 -1.4340683
< [5,] 0.12949534 0.98407916 0.68896865 -0.6770101 -0.5558435
< [6,] 0.33028037 -0.30845821 0.38447528 -0.4921896 -1.5800996
< [7,] -0.08177587 -3.18480533 -0.23714281 -0.6766834 6.0266247
< [8,] -0.26671047 0.37874819 0.05563528 -0.5386048 -1.1090987
< [9,] 1.14824861 0.59395989 0.30325377 0.1331989 -1.6170149
< [10,] -0.43484816 -0.40604574 -0.15242182 -0.4689142 -1.9367084
< [11,] -0.02830992 1.44823151 -0.64414378 -0.9173624 2.7356243
< [12,] 1.21038226 0.53698700 0.61290804 0.2053933 -1.7349394
< [13,] 0.53588538 -0.22511799 0.33108311 -0.3691168 -1.4085111
< [14,] -1.81448328 -1.30622711 -0.91955592 1.9573658 2.5804178
< [15,] -0.07784973 1.08536016 -0.45711876 -0.8394958 0.2020498
<
< $last.step$climb
< [1] -48430.31 -349283.31 -290796.00 315106.42 2729990.03
<
<
934c904
< [1] 100
---
> [1] 75
941,955c911,925
< [1,] -0.85305069 0.22530467 -0.07277460 -0.1440209 -0.9617952
< [2,] -1.70317169 0.04809838 -1.19012246 1.6812953 -1.0131651
< [3,] 1.75076609 0.33348239 1.72723960 1.8355312 1.8030823
< [4,] 0.15557624 -0.20256336 -0.43267850 -0.6892240 -1.4334619
< [5,] 0.12952780 0.98415978 0.68914447 -0.6770552 -0.5554817
< [6,] 0.33019303 -0.30874430 0.38449290 -0.4921534 -1.5796044
< [7,] -0.08175667 -3.18593246 -0.23721478 -0.6767793 6.0293191
< [8,] -0.26665324 0.37871286 0.05566401 -0.5386956 -1.1089755
< [9,] 1.14837008 0.59405413 0.30327821 0.1332233 -1.6168539
< [10,] -0.43487414 -0.40624201 -0.15241983 -0.4688578 -1.9364758
< [11,] -0.02826361 1.44860218 -0.64428011 -0.9175583 2.7372184
< [12,] 1.21036633 0.53706055 0.61286122 0.2052741 -1.7345782
< [13,] 0.53599855 -0.22525315 0.33115458 -0.3689835 -1.4082333
< [14,] -1.81469340 -1.30650135 -0.91962564 1.9578294 2.5813145
< [15,] -0.07773903 1.08568419 -0.45718024 -0.8396488 0.2028243
---
> [1,] -0.85234478 0.22391255 -0.07352168 -0.1446474 -0.9667939
> [2,] -1.70440691 0.04648408 -1.19187418 1.6836901 -1.0116930
> [3,] 1.75174657 0.33535241 1.72587454 1.8367494 1.7958201
> [4,] 0.15579094 -0.20309642 -0.43362554 -0.6891859 -1.4267967
> [5,] 0.12991963 0.98333538 0.68739315 -0.6767124 -0.5620972
> [6,] 0.33086011 -0.30311404 0.38387759 -0.4917565 -1.5823937
> [7,] -0.07989148 -3.18597288 -0.23681005 -0.6769023 6.0302925
> [8,] -0.26596451 0.37804584 0.05556194 -0.5387087 -1.1089943
> [9,] 1.14932504 0.59476363 0.30337878 0.1352853 -1.6147885
> [10,] -0.43413381 -0.40461336 -0.15239416 -0.4696682 -1.9371976
> [11,] -0.02782997 1.45111717 -0.64509342 -0.9178916 2.7444007
> [12,] 1.21065533 0.53914179 0.61120668 0.2059469 -1.7330972
> [13,] 0.53650159 -0.22510291 0.33108334 -0.3687683 -1.4084656
> [14,] -1.81538737 -1.30822940 -0.92054812 1.9588064 2.5784263
> [15,] -0.07753252 1.08785999 -0.45784326 -0.8400504 0.2086192
1021c991
< 0.37023 -1.68022 -2.24759 -0.12912 -0.01236
---
> 0.36750 -1.67993 -2.24379 -0.12947 -0.01241
1028c998
< Log-Likelihood: -73.19888
---
> Log-Likelihood: -73.19883
1032,1036c1002,1006
< (Intercept) 0.370232 0.474949 0.7795 0.4356739
< x1 -1.680221 0.209277 -8.0287 9.851e-16 ***
< x2 -2.247590 0.674143 -3.3340 0.0008561 ***
< logSigmaMu -0.129120 0.257991 -0.5005 0.6167339
< logSigmaNu -0.012365 0.129702 -0.0953 0.9240501
---
> (Intercept) 0.367502 0.474613 0.7743 0.4387426
> x1 -1.679929 0.209229 -8.0291 9.816e-16 ***
> x2 -2.243794 0.673969 -3.3292 0.0008709 ***
> logSigmaMu -0.129473 0.258047 -0.5017 0.6158482
> logSigmaNu -0.012409 0.129690 -0.0957 0.9237740
1052,1056c1022,1026
< (Intercept) 0.37023 0.47495 0.780 0.435674
< x1 -1.68022 0.20928 -8.029 9.85e-16 ***
< x2 -2.24759 0.67414 -3.334 0.000856 ***
< logSigmaMu -0.12912 0.25799 -0.500 0.616734
< logSigmaNu -0.01236 0.12970 -0.095 0.924050
---
> (Intercept) 0.36750 0.47461 0.774 0.438743
> x1 -1.67993 0.20923 -8.029 9.82e-16 ***
> x2 -2.24379 0.67397 -3.329 0.000871 ***
> logSigmaMu -0.12947 0.25805 -0.502 0.615848
> logSigmaNu -0.01241 0.12969 -0.096 0.923774
1062c1032
< Log-likelihood: -73.19888 on 5 Df
---
> Log-likelihood: -73.19883 on 5 Df
1066c1036
< 0.37023230 -1.68022057 -2.24759034 -0.12912036 -0.01236491
---
> 0.36750163 -1.67992931 -2.24379444 -0.12947348 -0.01240886
1069c1039
< 0.3702323 -1.6802206 -2.2475903 0.8788682 0.9877112
---
> 0.3675016 -1.6799293 -2.2437944 0.8785579 0.9876678
1072,1076c1042,1046
< (Intercept) 0.225577025 -0.020677468 -0.254981355 0.024060496 0.003049033
< x1 -0.020677468 0.043796732 0.008672537 -0.013420642 -0.002970066
< x2 -0.254981355 0.008672537 0.454469078 -0.017324835 -0.001686267
< logSigmaMu 0.024060496 -0.013420642 -0.017324835 0.066559175 -0.002625939
< logSigmaNu 0.003049033 -0.002970066 -0.001686267 -0.002625939 0.016822599
---
> (Intercept) 0.22525765 -0.020606031 -0.254727485 0.023900534 0.003010360
> x1 -0.02060603 0.043776857 0.008606687 -0.013409282 -0.002965503
> x2 -0.25472748 0.008606687 0.454234549 -0.017236296 -0.001593108
> logSigmaMu 0.02390053 -0.013409282 -0.017236296 0.066588439 -0.002635405
> logSigmaNu 0.00301036 -0.002965503 -0.001593108 -0.002635405 0.016819519
1079,1083c1049,1053
< (Intercept) 0.225577025 -0.020677468 -0.254981355 0.021146004 0.003011564
< x1 -0.020677468 0.043796732 0.008672537 -0.011794975 -0.002933567
< x2 -0.254981355 0.008672537 0.454469078 -0.015226246 -0.001665545
< sigmaMu 0.021146004 -0.011794975 -0.015226246 0.051410924 -0.002279493
< sigmaNu 0.003011564 -0.002933567 -0.001665545 -0.002279493 0.016411681
---
> (Intercept) 0.225257647 -0.020606031 -0.254727485 0.020998003 0.002973236
> x1 -0.020606031 0.043776857 0.008606687 -0.011780830 -0.002928932
> x2 -0.254727485 0.008606687 0.454234549 -0.015143084 -0.001573462
> sigmaMu 0.020998003 -0.011780830 -0.015143084 0.051397216 -0.002286802
> sigmaNu 0.002973236 -0.002928932 -0.001573462 -0.002286802 0.016407234
1085c1055
< 'log Lik.' -73.19888 (df=5)
---
> 'log Lik.' -73.19883 (df=5)
1087c1057
< [1] -40.0000 156.3978
---
> [1] -40.0000 156.3977
1090c1060
< [1] -73.19888
---
> [1] -73.19883
1094c1064
< 0.37023230 -1.68022057 -2.24759034 -0.12912036 -0.01236491
---
> 0.36750163 -1.67992931 -2.24379444 -0.12947348 -0.01240886
1098c1068
< -0.0080480603 -0.0013305834 0.0109845702 -0.0009545502 -0.0004683449
---
> -0.0014212306 -0.0034992596 0.0064419525 0.0003782988 0.0003341343
1102,1106c1072,1076
< (Intercept) -13.306993 -4.094966 -7.3016122 2.1350119 1.2902336
< x1 -4.094966 -26.068270 -1.9885298 -4.4813349 -4.7590560
< x2 -7.301612 -1.988530 -6.2332040 0.6336632 0.4464176
< logSigmaMu 2.135012 -4.481335 0.6336632 -16.6813720 -3.7185288
< logSigmaNu 1.290234 -4.759056 0.4464176 -3.7185288 -61.0536175
---
> (Intercept) -13.317517 -4.096146 -7.3057987 2.1155739 1.300861
> x1 -4.096146 -26.075639 -1.9898094 -4.4840349 -4.755412
> x2 -7.305799 -1.989809 -6.2353998 0.6259168 0.464233
> logSigmaMu 2.115574 -4.484035 0.6259168 -16.6651955 -3.721179
> logSigmaNu 1.300861 -4.755412 0.4642330 -3.7211788 -61.065093
1129,1143c1099,1113
< [1,] 0.85199137 -0.22379118 0.07345967 -0.1446569 -0.9676550
< [2,] 1.70281635 -0.04674831 1.19066184 1.6820349 -1.0125029
< [3,] -1.74991751 -0.33326384 -1.72490952 1.8352014 1.7951045
< [4,] -0.15548576 0.20323447 0.43364056 -0.6890178 -1.4278996
< [5,] -0.12989065 -0.98291215 -0.68740126 -0.6768874 -0.5617200
< [6,] -0.33011912 0.30573161 -0.38378812 -0.4918887 -1.5822020
< [7,] 0.07979653 3.18602171 0.23679061 -0.6772242 6.0320587
< [8,] 0.26554601 -0.37782492 -0.05576143 -0.5390741 -1.1085099
< [9,] -1.14876154 -0.59374960 -0.30323926 0.1347705 -1.6153056
< [10,] 0.43355401 0.40484513 0.15201143 -0.4698409 -1.9368856
< [11,] 0.02771595 -1.45035959 0.64470552 -0.9184525 2.7423588
< [12,] -1.20985117 -0.53838077 -0.61106296 0.2048135 -1.7333264
< [13,] -0.53665128 0.22536070 -0.33121654 -0.3682552 -1.4085157
< [14,] 1.81419999 1.30762331 0.91981070 1.9582763 2.5771097
< [15,] 0.07700874 -1.08711714 0.45728334 -0.8407535 0.2074227
---
> [1,] 0.85278081 -0.2247850 0.07302970 -0.1442070 -0.9634923
> [2,] 1.70342425 -0.0476419 1.19055345 1.6820162 -1.0127268
> [3,] -1.75059965 -0.3340379 -1.72645582 1.8351650 1.8000202
> [4,] -0.15552297 0.2026892 0.43296702 -0.6893599 -1.4315786
> [5,] -0.12953233 -0.9838683 -0.68846571 -0.6770129 -0.5576955
> [6,] -0.33020957 0.3070305 -0.38415893 -0.4921914 -1.5806796
> [7,] 0.08124385 3.1854369 0.23706941 -0.6768114 6.0284476
> [8,] 0.26650783 -0.3785437 -0.05560267 -0.5386742 -1.1090288
> [9,] -1.14849813 -0.5942606 -0.30325840 0.1336487 -1.6163416
> [10,] 0.43466534 0.4056715 0.15242875 -0.4690608 -1.9368240
> [11,] 0.02815366 -1.4492071 0.64446998 -0.9176305 2.7387662
> [12,] -1.21036511 -0.5376472 -0.61231215 0.2052291 -1.7342086
> [13,] -0.53592238 0.2250517 -0.33100094 -0.3690601 -1.4085335
> [14,] 1.81473915 1.3068211 0.91982779 1.9580283 2.5799493
> [15,] 0.07771403 -1.0862084 0.45735047 -0.8397008 0.2042601
1210c1180
< -4.63363 -1.68002 -2.24180 -0.12949 -0.01249
---
> -4.63391 -1.68002 -2.24127 -0.12953 -0.01241
1215,1218c1185,1186
< BFGSR maximization, 100 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
---
> BFGSR maximization, 73 iterations
> Return code 2: successive function values within tolerance limit
1223,1227c1191,1195
< (Intercept) -4.633634 0.474516 -9.7650 < 2.2e-16 ***
< x1 -1.680023 0.209215 -8.0301 9.737e-16 ***
< x2 -2.241803 0.673880 -3.3267 0.0008788 ***
< logSigmaMu -0.129488 0.258035 -0.5018 0.6157922
< logSigmaNu -0.012488 0.129680 -0.0963 0.9232824
---
> (Intercept) -4.633912 0.474500 -9.7659 < 2.2e-16 ***
> x1 -1.680022 0.209226 -8.0297 9.772e-16 ***
> x2 -2.241274 0.673908 -3.3258 0.0008817 ***
> logSigmaMu -0.129526 0.258065 -0.5019 0.6157303
> logSigmaNu -0.012412 0.129690 -0.0957 0.9237579
1243,1247c1211,1215
< (Intercept) -4.63363 0.47452 -9.765 < 2e-16 ***
< x1 -1.68002 0.20921 -8.030 9.74e-16 ***
< x2 -2.24180 0.67388 -3.327 0.000879 ***
< logSigmaMu -0.12949 0.25803 -0.502 0.615792
< logSigmaNu -0.01249 0.12968 -0.096 0.923282
---
> (Intercept) -4.63391 0.47450 -9.766 < 2e-16 ***
> x1 -1.68002 0.20923 -8.030 9.77e-16 ***
> x2 -2.24127 0.67391 -3.326 0.000882 ***
> logSigmaMu -0.12953 0.25807 -0.502 0.615730
> logSigmaNu -0.01241 0.12969 -0.096 0.923758
1251,1254c1219,1220
< BFGSR maximization, 100 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
---
> BFGSR maximization, 73 iterations
> Return code 2: successive function values within tolerance limit
1259c1225
< -4.63363402 -1.68002313 -2.24180291 -0.12948769 -0.01248821
---
> -4.63391165 -1.68002232 -2.24127447 -0.12952582 -0.01241152
1262c1228
< -4.6336340 -1.6800231 -2.2418029 0.8785454 0.9875894
---
> -4.6339117 -1.6800223 -2.2412745 0.8785119 0.9876652
1265,1269c1231,1235
< (Intercept) 0.225165667 -0.020585730 -0.254631964 0.023855252 0.002986321
< x1 -0.020585730 0.043770852 0.008580805 -0.013404055 -0.002969232
< x2 -0.254631964 0.008580805 0.454114349 -0.017198112 -0.001539042
< logSigmaMu 0.023855252 -0.013404055 -0.017198112 0.066581904 -0.002635515
< logSigmaNu 0.002986321 -0.002969232 -0.001539042 -0.002635515 0.016816996
---
> (Intercept) 0.225149823 -0.020580559 -0.254635601 0.023847765 0.002981648
> x1 -0.020580559 0.043775600 0.008573460 -0.013405916 -0.002969797
> x2 -0.254635601 0.008573460 0.454151985 -0.017194816 -0.001524188
> logSigmaMu 0.023847765 -0.013405916 -0.017194816 0.066597765 -0.002638193
> logSigmaNu 0.002981648 -0.002969797 -0.001524188 -0.002638193 0.016819556
1272,1276c1238,1242
< (Intercept) 0.225165667 -0.020585730 -0.254631964 0.020957922 0.002949259
< x1 -0.020585730 0.043770852 0.008580805 -0.011776071 -0.002932382
< x2 -0.254631964 0.008580805 0.454114349 -0.015109322 -0.001519942
< sigmaMu 0.020957922 -0.011776071 -0.015109322 0.051390712 -0.002286684
< sigmaNu 0.002949259 -0.002932382 -0.001519942 -0.002286684 0.016402169
---
> (Intercept) 0.22514982 -0.020580559 -0.254635601 0.020950545 0.002944870
> x1 -0.02058056 0.043775600 0.008573460 -0.011777256 -0.002933165
> x2 -0.25463560 0.008573460 0.454151985 -0.015105851 -0.001505387
> sigmaMu 0.02095055 -0.011777256 -0.015105851 0.051399034 -0.002289095
> sigmaNu 0.00294487 -0.002933165 -0.001505387 -0.002289095 0.016407183
1287c1253
< -4.63363402 -1.68002313 -2.24180291 -0.12948769 -0.01248821
---
> -4.63391165 -1.68002232 -2.24127447 -0.12952582 -0.01241152
1291c1257
< -5.956686e-04 7.749401e-05 2.461182e-03 1.764174e-04 5.133549e-03
---
> -7.425390e-04 -5.237316e-05 1.205358e-03 2.666987e-04 4.763349e-04
1295,1299c1261,1265
< (Intercept) -13.320003 -4.096850 -7.3070098 2.1118076 1.3042287
< x1 -4.096850 -26.079326 -1.9904015 -4.4849891 -4.7621248
< x2 -7.307010 -1.990401 -6.2364004 0.6251604 0.4733692
< logSigmaMu 2.111808 -4.484989 0.6251604 -16.6644476 -3.7212812
< logSigmaNu 1.304229 -4.762125 0.4733692 -3.7212812 -61.0759302
---
> (Intercept) -13.321012 -4.096571 -7.3072433 2.1105735 1.306995
> x1 -4.096571 -26.076360 -1.9903898 -4.4846924 -4.761848
> x2 -7.307243 -1.990390 -6.2361292 0.6247544 0.476812
> logSigmaMu 2.110574 -4.484692 0.6247544 -16.6602022 -3.722583
> logSigmaNu 1.306995 -4.761848 0.4768120 -3.7225828 -61.067774
1302c1268
< [1] 3
---
> [1] 2
1305c1271
< [1] "Last step could not find a value above the current.\nBoundary of parameter space? \nConsider switching to a more robust optimisation method temporarily."
---
> [1] "successive function values within tolerance limit"
1308,1310c1274
< $last.step$theta0
< (Intercept) x1 x2 logSigmaMu logSigmaNu
< -4.6336312 -1.6800028 -2.2417860 -0.1294694 -0.0123293
---
> NULL
1312,1335d1275
< $last.step$f0
< [1] -73.19882
< attr(,"gradient")
< [,1] [,2] [,3] [,4] [,5]
< [1,] 0.85285116 -0.22520391 0.07277818 -0.1441324 -0.9622137
< [2,] 1.70306444 -0.04811529 1.19001042 1.6810528 -1.0131173
< [3,] -1.75047981 -0.33380319 -1.72688570 1.8348800 1.8021747
< [4,] -0.15571531 0.20249726 0.43241948 -0.6891767 -1.4340683
< [5,] -0.12949534 -0.98407916 -0.68896865 -0.6770101 -0.5558435
< [6,] -0.33028037 0.30845821 -0.38447528 -0.4921896 -1.5800996
< [7,] 0.08177587 3.18480533 0.23714281 -0.6766834 6.0266247
< [8,] 0.26671047 -0.37874819 -0.05563528 -0.5386048 -1.1090987
< [9,] -1.14824861 -0.59395989 -0.30325377 0.1331989 -1.6170149
< [10,] 0.43484816 0.40604574 0.15242182 -0.4689142 -1.9367084
< [11,] 0.02830992 -1.44823151 0.64414378 -0.9173624 2.7356243
< [12,] -1.21038226 -0.53698700 -0.61290804 0.2053933 -1.7349394
< [13,] -0.53588538 0.22511799 -0.33108311 -0.3691168 -1.4085111
< [14,] 1.81448328 1.30622711 0.91955592 1.9573658 2.5804178
< [15,] 0.07784973 -1.08536016 0.45711876 -0.8394958 0.2020498
<
< $last.step$climb
< [1] 48430.31 349283.31 290796.00 315106.42 2729990.03
<
<
1341c1281
< [1] 100
---
> [1] 73
1348,1362c1288,1302
< [1,] 0.85305069 -0.22530467 0.07277460 -0.1440209 -0.9617952
< [2,] 1.70317169 -0.04809838 1.19012246 1.6812953 -1.0131651
< [3,] -1.75076609 -0.33348239 -1.72723960 1.8355312 1.8030823
< [4,] -0.15557624 0.20256336 0.43267850 -0.6892240 -1.4334619
< [5,] -0.12952780 -0.98415978 -0.68914447 -0.6770552 -0.5554817
< [6,] -0.33019303 0.30874430 -0.38449290 -0.4921534 -1.5796044
< [7,] 0.08175667 3.18593246 0.23721478 -0.6767793 6.0293191
< [8,] 0.26665324 -0.37871286 -0.05566401 -0.5386956 -1.1089755
< [9,] -1.14837008 -0.59405413 -0.30327821 0.1332233 -1.6168539
< [10,] 0.43487414 0.40624201 0.15241983 -0.4688578 -1.9364758
< [11,] 0.02826361 -1.44860218 0.64428011 -0.9175583 2.7372184
< [12,] -1.21036633 -0.53706055 -0.61286122 0.2052741 -1.7345782
< [13,] -0.53599855 0.22525315 -0.33115458 -0.3689835 -1.4082333
< [14,] 1.81469340 1.30650135 0.91962564 1.9578294 2.5813145
< [15,] 0.07773903 -1.08568419 0.45718024 -0.8396488 0.2028243
---
> [1,] 0.85300597 -0.22538442 0.07270967 -0.1440551 -0.9615875
> [2,] 1.70313415 -0.04819704 1.19001008 1.6809910 -1.0132088
> [3,] -1.75081925 -0.33365931 -1.72733510 1.8354213 1.8035220
> [4,] -0.15575929 0.20248810 0.43239154 -0.6891027 -1.4343552
> [5,] -0.12954290 -0.98419670 -0.68923518 -0.6769998 -0.5551304
> [6,] -0.33034949 0.30889860 -0.38462520 -0.4921179 -1.5796319
> [7,] 0.08189456 3.18535013 0.23720553 -0.6766812 6.0277787
> [8,] 0.26673068 -0.37878111 -0.05566019 -0.5386220 -1.1090629
> [9,] -1.14832130 -0.59395010 -0.30328878 0.1331873 -1.6170652
> [10,] 0.43493369 0.40626633 0.15243113 -0.4688524 -1.9365296
> [11,] 0.02832945 -1.44822208 0.64415440 -0.9173654 2.7358109
> [12,] -1.21044619 -0.53688713 -0.61307141 0.2055182 -1.7349351
> [13,] -0.53600998 0.22524959 -0.33118372 -0.3690370 -1.4082862
> [14,] 1.81463246 1.30632858 0.91958449 1.9574877 2.5811938
> [15,] 0.07784490 -1.08535582 0.45711810 -0.8395052 0.2019637
1429c1369
< -0.231803 1.892830 1.966575 0.001321 0.052660
---
> -0.233782 1.893280 1.969602 0.001543 0.052867
1434,1436c1374,1378
< BFGSR maximization, 92 iterations
< Return code 2: successive function values within tolerance limit
< Log-Likelihood: -64.31275
---
> BFGSR maximization, 96 iterations
> Return code 3: Last step could not find a value above the current.
> Boundary of parameter space?
> Consider switching to a more robust optimisation method temporarily.
> Log-Likelihood: -64.31273
1440,1444c1382,1386
< (Intercept) -0.2318034 0.5479951 -0.4230 0.67229
< x1 1.8928298 0.3009767 6.2890 3.196e-10 ***
< x2 1.9665747 0.8183929 2.4030 0.01626 *
< logSigmaMu 0.0013212 0.2778784 0.0048 0.99621
< logSigmaNu 0.0526605 0.1629825 0.3231 0.74662
---
> (Intercept) -0.2337822 0.5483289 -0.4264 0.66985
> x1 1.8932801 0.3011173 6.2875 3.226e-10 ***
> x2 1.9696025 0.8188341 2.4054 0.01616 *
> logSigmaMu 0.0015433 0.2778758 0.0056 0.99557
> logSigmaNu 0.0528675 0.1630158 0.3243 0.74570
1460,1464c1402,1406
< (Intercept) -0.231803 0.547995 -0.423 0.6723
< x1 1.892830 0.300977 6.289 3.2e-10 ***
< x2 1.966575 0.818393 2.403 0.0163 *
< logSigmaMu 0.001321 0.277878 0.005 0.9962
< logSigmaNu 0.052660 0.162982 0.323 0.7466
---
> (Intercept) -0.233782 0.548329 -0.426 0.6698
> x1 1.893280 0.301117 6.288 3.23e-10 ***
> x2 1.969602 0.818834 2.405 0.0162 *
> logSigmaMu 0.001543 0.277876 0.006 0.9956
> logSigmaNu 0.052867 0.163016 0.324 0.7457
1468,1470c1410,1414
< BFGSR maximization, 92 iterations
< Return code 2: successive function values within tolerance limit
< Log-likelihood: -64.31275 on 5 Df
---
> BFGSR maximization, 96 iterations
> Return code 3: Last step could not find a value above the current.
> Boundary of parameter space?
> Consider switching to a more robust optimisation method temporarily.
> Log-likelihood: -64.31273 on 5 Df
1484,1488c1428,1432
< (Intercept) -0.2318 0.5480 -0.423 0.67229
< x1 1.8928 0.3010 6.289 3.20e-10 ***
< x2 1.9666 0.8184 2.403 0.01626 *
< sigmaMu 1.0013 0.2782 3.599 0.00032 ***
< sigmaNu 1.0541 0.1718 6.136 8.48e-10 ***
---
> (Intercept) -0.2338 0.5483 -0.426 0.66985
> x1 1.8933 0.3011 6.288 3.23e-10 ***
> x2 1.9696 0.8188 2.405 0.01616 *
> sigmaMu 1.0015 0.2783 3.599 0.00032 ***
> sigmaNu 1.0543 0.1719 6.134 8.55e-10 ***
1492,1494c1436,1440
< BFGSR maximization, 92 iterations
< Return code 2: successive function values within tolerance limit
< Log-likelihood: -64.31275 on 5 Df
---
> BFGSR maximization, 96 iterations
> Return code 3: Last step could not find a value above the current.
> Boundary of parameter space?
> Consider switching to a more robust optimisation method temporarily.
> Log-likelihood: -64.31273 on 5 Df
1498c1444
< -0.23180342 1.89282980 1.96657471 0.00132116 0.05266047
---
> -0.23378216 1.89328013 1.96960246 0.00154326 0.05286747
1501c1447
< -0.2318034 1.8928298 1.9665747 1.0013220 1.0540717
---
> -0.2337822 1.8932801 1.9696025 1.0015445 1.0542899
1504,1508c1450,1454
< (Intercept) 0.30029863 -0.03127137 -0.36361260 -0.015830061 -0.016309724
< x1 -0.03127137 0.09058698 0.03162888 0.035167089 0.015903594
< x2 -0.36361260 0.03162888 0.66976692 0.018504060 0.024364246
< logSigmaMu -0.01583006 0.03516709 0.01850406 0.077216406 0.004321731
< logSigmaNu -0.01630972 0.01590359 0.02436425 0.004321731 0.026563285
---
> (Intercept) 0.30066457 -0.03140943 -0.36406867 -0.015974524 -0.016384019
> x1 -0.03140943 0.09067161 0.03182344 0.035194978 0.015930682
> x2 -0.36406867 0.03182344 0.67048933 0.018652238 0.024503878
> logSigmaMu -0.01597452 0.03519498 0.01865224 0.077214979 0.004337456
> logSigmaNu -0.01638402 0.01593068 0.02450388 0.004337456 0.026574149
1511,1515c1457,1461
< (Intercept) 0.30029863 -0.03127137 -0.36361260 -0.015850989 -0.017191619
< x1 -0.03127137 0.09058698 0.03162888 0.035213581 0.016763528
< x2 -0.36361260 0.03162888 0.66976692 0.018528523 0.025681662
< sigmaMu -0.01585099 0.03521358 0.01852852 0.077420706 0.004561437
< sigmaNu -0.01719162 0.01676353 0.02568166 0.004561437 0.029513593
---
> (Intercept) 0.30066457 -0.03140943 -0.36406867 -0.015999196 -0.017273506
> x1 -0.03140943 0.09067161 0.03182344 0.035249335 0.016795557
> x2 -0.36406867 0.03182344 0.67048933 0.018681045 0.025834191
> sigmaMu -0.01599920 0.03524934 0.01868105 0.077453673 0.004579999
> sigmaNu -0.01727351 0.01679556 0.02583419 0.004579999 0.029537890
1518,1522c1464,1468
< (Intercept) -0.23180342 0.5479951 -0.423002731 6.722933e-01
< x1 1.89282980 0.3009767 6.288957858 3.196042e-10
< x2 1.96657471 0.8183929 2.402971401 1.626246e-02
< logSigmaMu 0.00132116 0.2778784 0.004754453 9.962065e-01
< logSigmaNu 0.05266047 0.1629825 0.323105096 7.466157e-01
---
> (Intercept) -0.23378216 0.5483289 -0.426353903 6.698500e-01
> x1 1.89328013 0.3011173 6.287517678 3.225823e-10
> x2 1.96960246 0.8188341 2.405374171 1.615591e-02
> logSigmaMu 0.00154326 0.2778758 0.005553777 9.955687e-01
> logSigmaNu 0.05286747 0.1630158 0.324308863 7.457042e-01
1525,1529c1471,1475
< (Intercept) -0.2318034 0.5479951 -0.4230027 6.722933e-01
< x1 1.8928298 0.3009767 6.2889579 3.196042e-10
< x2 1.9665747 0.8183929 2.4029714 1.626246e-02
< sigmaMu 1.0013220 0.2782458 3.5986964 3.198163e-04
< sigmaNu 1.0540717 0.1717952 6.1356293 8.482277e-10
---
> (Intercept) -0.2337822 0.5483289 -0.4263539 6.698500e-01
> x1 1.8932801 0.3011173 6.2875177 3.225823e-10
> x2 1.9696025 0.8188341 2.4053742 1.615591e-02
> sigmaMu 1.0015445 0.2783050 3.5987296 3.197754e-04
> sigmaNu 1.0542899 0.1718659 6.1343749 8.549467e-10
1531c1477
< 'log Lik.' -64.31275 (df=5)
---
> 'log Lik.' -64.31273 (df=5)
1536c1482
< [1] -64.31275
---
> [1] -64.31273
1540c1486
< -0.23180342 1.89282980 1.96657471 0.00132116 0.05266047
---
> -0.23378216 1.89328013 1.96960246 0.00154326 0.05286747
1544c1490
< -0.0057217520 0.0001722985 0.0053933537 0.0033756785 -0.0006327734
---
> -0.002894857 -0.002369745 0.002610000 0.003016516 -0.002543448
1548,1552c1494,1498
< (Intercept) -9.93670160 -1.4932084 -5.3103903 -0.06625682 -0.3255426
< x1 -1.49320839 -15.1474818 -0.5468229 6.29662070 7.6291849
< x2 -5.31039032 -0.5468229 -4.3934299 0.15322371 1.0716244
< logSigmaMu -0.06625682 6.2966207 0.1532237 -15.79127962 -1.3818716
< logSigmaNu -0.32554258 7.6291849 1.0716244 -1.38187156 -43.1715511
---
> (Intercept) -9.92921213 -1.4915778 -5.3068262 -0.07430279 -0.3220588
> x1 -1.49157779 -15.1380768 -0.5453987 6.29452164 7.6308755
> x2 -5.30682618 -0.5453987 -4.3907451 0.15071751 1.0791686
> logSigmaMu -0.07430279 6.2945216 0.1507175 -15.79417345 -1.3802899
> logSigmaNu -0.32205878 7.6308755 1.0791686 -1.38028985 -43.1734818
1555c1501
< [1] 2
---
> [1] 3
1558c1504
< [1] "successive function values within tolerance limit"
---
> [1] "Last step could not find a value above the current.\nBoundary of parameter space? \nConsider switching to a more robust optimisation method temporarily."
1561c1507,1509
< NULL
---
> $last.step$theta0
> (Intercept) x1 x2 logSigmaMu logSigmaNu
> -0.233805135 1.893310605 1.969641022 0.001551443 0.052675686
1562a1511,1534
> $last.step$f0
> [1] -64.31273
> attr(,"gradient")
> [,1] [,2] [,3] [,4] [,5]
> [1,] -0.85417510 -0.10609337 -0.18146777 -0.0235494 -0.8369719
> [2,] -1.41680128 -0.02702422 -0.97196805 1.4567554 -1.1645981
> [3,] 1.29745993 1.02088535 0.92544703 1.0920903 0.1540724
> [4,] 0.07075595 -0.25207707 -0.39840982 -0.7015966 -1.8261020
> [5,] 0.08922410 0.80745931 0.64769792 -0.6906630 -0.2847701
> [6,] 0.55923778 0.49468626 0.42897976 -0.2914444 -0.3603540
> [7,] -0.12034788 -3.06219247 -0.23674144 -0.7063845 6.3455056
> [8,] -0.20961505 0.33550846 0.08326478 -0.5906480 -1.0295346
> [9,] 1.03436546 0.66021829 0.28832659 0.1971790 -1.2970105
> [10,] -0.42828980 -0.58564682 -0.11733332 -0.3957152 -1.8006439
> [11,] -0.04064163 1.09509187 -0.50821521 -0.8668820 2.0017961
> [12,] 1.14034027 0.50533928 0.83221911 0.5852838 -0.7450190
> [13,] 0.53486256 -0.28181457 0.34791505 -0.2865027 -1.4336469
> [14,] -1.63819150 -1.34761986 -0.83803596 2.1201245 2.7646850
> [15,] -0.02103951 0.73904950 -0.29933851 -0.8946959 -0.4814000
>
> $last.step$climb
> [1] -394657.2 523581.9 662476.4 140569.0 -3294770.3
>
>
1568c1540
< [1] 92
---
> [1] 96
1575,1589c1547,1561
< [1,] -0.85456048 -0.10574838 -0.18128596 -0.02318625 -0.8359293
< [2,] -1.41689260 -0.02595057 -0.97159027 1.45595318 -1.1648211
< [3,] 1.29770902 1.02175888 0.92591976 1.09197185 0.1543521
< [4,] 0.07098775 -0.25157887 -0.39776282 -0.70163382 -1.8288917
< [5,] 0.08898377 0.80812716 0.64830137 -0.69076306 -0.2824851
< [6,] 0.55957698 0.49454384 0.42929716 -0.29130086 -0.3594897
< [7,] -0.12114104 -3.06130255 -0.23685544 -0.70588067 6.3408188
< [8,] -0.21016870 0.33599431 0.08322582 -0.59041343 -1.0297910
< [9,] 1.03421264 0.66078386 0.28834187 0.19628370 -1.2974237
< [10,] -0.42871894 -0.58584523 -0.11748153 -0.39549761 -1.8006173
< [11,] -0.04106389 1.09436723 -0.50815300 -0.86610364 1.9999150
< [12,] 1.14072160 0.50491164 0.83299071 0.58566577 -0.7446499
< [13,] 0.53435524 -0.28152752 0.34775678 -0.28708940 -1.4337425
< [14,] -1.63832120 -1.34692530 -0.83794574 2.11935609 2.7651239
< [15,] -0.02140189 0.73856379 -0.29936537 -0.89398617 -0.4830013
---
> [1,] -0.85399301 -0.10602099 -0.18140766 -0.02364687 -0.8371385
> [2,] -1.41680831 -0.02700922 -0.97193915 1.45664700 -1.1645431
> [3,] 1.29738032 1.02095947 0.92539297 1.09190281 0.1539769
> [4,] 0.07100562 -0.25197861 -0.39807733 -0.70154825 -1.8266607
> [5,] 0.08922699 0.80745668 0.64756678 -0.69055935 -0.2850413
> [6,] 0.55925418 0.49480489 0.42892323 -0.29147726 -0.3608594
> [7,] -0.12039508 -3.06089075 -0.23666324 -0.70622873 6.3420715
> [8,] -0.20969533 0.33555238 0.08322106 -0.59050851 -1.0297117
> [9,] 1.03428932 0.66016070 0.28831450 0.19721031 -1.2971304
> [10,] -0.42828624 -0.58538485 -0.11736408 -0.39582567 -1.8009247
> [11,] -0.04081588 1.09472020 -0.50816401 -0.86667778 2.0006839
> [12,] 1.14045635 0.50528295 0.83226925 0.58550194 -0.7452782
> [13,] 0.53470207 -0.28162570 0.34780933 -0.28674186 -1.4339655
> [14,] -1.63795687 -1.34717561 -0.83791582 2.11940059 2.7641334
> [15,] -0.02125898 0.73877872 -0.29935581 -0.89443186 -0.4821556
1656,1660c1628,1632
< [1] "Component 1: Mean relative difference: 1.094632e-06"
< [2] "Component 2: Mean relative difference: 0.001558529"
< [3] "Component 3: Mean relative difference: 0.5539907"
< [4] "Component 4: Mean relative difference: 0.0008698725"
< [5] "Component 9: Mean relative difference: 0.21875"
---
> [1] "Component 1: Mean relative difference: 1.585932e-07"
> [2] "Component 2: Mean relative difference: 0.0009942645"
> [3] "Component 3: Mean relative difference: 5.267562"
> [4] "Component 4: Mean relative difference: 0.000453646"
> [5] "Component 9: Mean relative difference: 0.2352941"
1662c1634
< [1] "Mean relative difference: 0.001058863"
---
> [1] "Mean relative difference: 0.0006692936"
1696c1668
< [1] -8.012589e-05
---
> [1] 1.160884e-05
1698c1670
< [1] 8.012589e-05
---
> [1] -1.160884e-05
1722c1694
< -0.223091 1.640552 2.109126 -0.167587 -0.001229
---
> -0.223438 1.640494 2.109440 -0.167351 -0.001139
1727,1731c1699,1701
< BFGSR maximization, 94 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
< Log-Likelihood: -71.19257
---
> BFGSR maximization, 91 iterations
> Return code 2: successive function values within tolerance limit
> Log-Likelihood: -71.19256
1735,1739c1705,1709
< (Intercept) -0.2230912 0.4724798 -0.4722 0.636805
< x1 1.6405516 0.2110374 7.7737 7.62e-15 ***
< x2 2.1091259 0.6847980 3.0799 0.002071 **
< logSigmaMu -0.1675868 0.2715360 -0.6172 0.537116
< logSigmaNu -0.0012291 0.1322653 -0.0093 0.992586
---
> (Intercept) -0.2234379 0.4725748 -0.4728 0.63635
> x1 1.6404941 0.2110522 7.7729 7.669e-15 ***
> x2 2.1094395 0.6848755 3.0800 0.00207 **
> logSigmaMu -0.1673511 0.2714906 -0.6164 0.53762
> logSigmaNu -0.0011386 0.1322729 -0.0086 0.99313
1754,1758c1724,1728
< (Intercept) -0.223091 0.472480 -0.472 0.63680
< x1 1.640552 0.211037 7.774 7.62e-15 ***
< x2 2.109126 0.684798 3.080 0.00207 **
< logSigmaMu -0.167587 0.271536 -0.617 0.53712
< logSigmaNu -0.001229 0.132265 -0.009 0.99259
---
> (Intercept) -0.223438 0.472575 -0.473 0.63635
> x1 1.640494 0.211052 7.773 7.67e-15 ***
> x2 2.109440 0.684875 3.080 0.00207 **
> logSigmaMu -0.167351 0.271491 -0.616 0.53762
> logSigmaNu -0.001139 0.132273 -0.009 0.99313
1762,1766c1732,1734
< BFGSR maximization, 94 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
< Log-likelihood: -71.19257 on 5 Df
---
> BFGSR maximization, 91 iterations
> Return code 2: successive function values within tolerance limit
> Log-likelihood: -71.19256 on 5 Df
1769c1737
< 'log Lik.' -71.19257 (df=5)
---
> 'log Lik.' -71.19256 (df=5)
1774c1742
< [1] -71.19257
---
> [1] -71.19256
1778c1746
< -0.223091243 1.640551584 2.109125911 -0.167586773 -0.001229062
---
> -0.223437886 1.640494086 2.109439512 -0.167351143 -0.001138553
1782c1750
< -0.004597081 -0.003595316 0.003718896 0.002559430 0.005775754
---
> -0.0023645994 0.0002134735 0.0043525355 -0.0012274752 -0.0003310896
1786,1790c1754,1758
< (Intercept) -13.794706 -4.347789 -7.5305011 -1.1078594 -1.941168
< x1 -4.347789 -25.816430 -2.0581070 4.6518618 4.058639
< x2 -7.530501 -2.058107 -6.2675453 -0.1419137 -1.057720
< logSigmaMu -1.107859 4.651862 -0.1419137 -14.9259025 -3.778981
< logSigmaNu -1.941168 4.058639 -1.0577199 -3.7789812 -58.843429
---
> (Intercept) -13.788369 -4.345893 -7.5273217 -1.1108512 -1.941872
> x1 -4.345893 -25.811539 -2.0571716 4.6503075 4.052490
> x2 -7.527322 -2.057172 -6.2654750 -0.1435365 -1.057070
> logSigmaMu -1.110851 4.650307 -0.1435365 -14.9303962 -3.772496
> logSigmaNu -1.941872 4.052490 -1.0570698 -3.7724962 -58.832591
1793c1761
< [1] 3
---
> [1] 2
1796c1764
< [1] "Last step could not find a value above the current.\nBoundary of parameter space? \nConsider switching to a more robust optimisation method temporarily."
---
> [1] "successive function values within tolerance limit"
1799,1801c1767
< $last.step$theta0
< (Intercept) x1 x2 logSigmaMu logSigmaNu
< -0.223069263 1.640567630 2.109139521 -0.167590079 -0.001104798
---
> NULL
1803,1826d1768
< $last.step$f0
< [1] -71.19257
< attr(,"gradient")
< [,1] [,2] [,3] [,4] [,5]
< [1,] -0.50890347 0.088076144 0.10311628 -0.39394139 -0.53199432
< [2,] -1.81782207 0.066203684 -1.24798830 1.79963449 -0.96102770
< [3,] 1.78475923 0.484635801 1.76949162 1.73296567 1.89483662
< [4,] 0.15192066 -0.162870108 -0.39617342 -0.73695118 -1.58481429
< [5,] 0.08163734 1.038553936 0.69764082 -0.67798075 -0.44789222
< [6,] 0.33239284 -0.232166618 0.37367793 -0.53994844 -1.57384483
< [7,] -0.18038095 -3.029826586 -0.24852000 -0.62221850 5.48203398
< [8,] 0.01868297 -0.004072419 0.01068545 -0.41762045 -0.58178126
< [9,] 1.11617948 0.666208024 0.29579687 0.06380248 -1.68540657
< [10,] -0.53814794 -0.420433630 -0.20444711 -0.40630808 -1.97423554
< [11,] -0.08314740 1.378785897 -0.64775877 -0.82308202 2.49613246
< [12,] 1.25914479 0.532034275 0.66943663 0.23086478 -1.79380274
< [13,] 0.44680728 -0.163449881 0.28640137 -0.46823638 -1.45043843
< [14,] -1.89352902 -1.288399766 -0.96278868 1.98467264 2.68174227
< [15,] -0.17490384 1.043077166 -0.49526660 -0.72346530 0.02897749
<
< $last.step$climb
< [1] 377614.78 275654.77 233805.01 -56786.32 2134847.49
<
<
1832c1774
< [1] 94
---
> [1] 91
1839,1853c1781,1795
< [1,] -0.50890540 0.088234245 0.10321613 -0.3939834 -0.53172119
< [2,] -1.81782335 0.066295337 -1.24799939 1.7996684 -0.96110368
< [3,] 1.78499551 0.484517917 1.76978692 1.7335751 1.89550772
< [4,] 0.15185082 -0.162894040 -0.39633434 -0.7369903 -1.58440000
< [5,] 0.08169718 1.038668778 0.69781919 -0.6780342 -0.44749097
< [6,] 0.33239191 -0.232226341 0.37371243 -0.5398692 -1.57348604
< [7,] -0.18033824 -3.030613705 -0.24856363 -0.6223050 5.48380019
< [8,] 0.01870093 -0.004076335 0.01069572 -0.4176825 -0.58171811
< [9,] 1.11631351 0.666354420 0.29582974 0.0638517 -1.68520814
< [10,] -0.53811240 -0.420524498 -0.20442093 -0.4063186 -1.97408530
< [11,] -0.08305281 1.379123273 -0.64784503 -0.8232512 2.49740257
< [12,] 1.25916822 0.532110486 0.66942673 0.2308431 -1.79348374
< [13,] 0.44687281 -0.163528621 0.28644563 -0.4681527 -1.45023663
< [14,] -1.89357920 -1.288384085 -0.96275217 1.9848032 2.68239268
< [15,] -0.17477659 1.043347852 -0.49529811 -0.7235949 0.02960641
---
> [1,] -0.50851468 0.088549089 0.10332418 -0.39424112 -0.5321531
> [2,] -1.81705349 0.066630144 -1.24744468 1.79880183 -0.9613088
> [3,] 1.78438158 0.484622552 1.76921902 1.73324126 1.8938711
> [4,] 0.15178686 -0.162863846 -0.39633296 -0.73697159 -1.5844197
> [5,] 0.08174549 1.038619943 0.69766179 -0.67810229 -0.4478988
> [6,] 0.33238733 -0.231741427 0.37360317 -0.53970858 -1.5740604
> [7,] -0.18005740 -3.029939879 -0.24845697 -0.62247948 5.4823898
> [8,] 0.01878553 -0.004094775 0.01074411 -0.41775131 -0.5816437
> [9,] 1.11613611 0.666458518 0.29576147 0.06379078 -1.6850635
> [10,] -0.53761405 -0.420066528 -0.20419807 -0.40660173 -1.9743628
> [11,] -0.08280126 1.379236916 -0.64772340 -0.82356321 2.4973552
> [12,] 1.25885598 0.532122184 0.66915527 0.23058826 -1.7934726
> [13,] 0.44678737 -0.163413157 0.28637417 -0.46810019 -1.4504984
> [14,] -1.89274932 -1.287262705 -0.96222366 1.98378247 2.6810702
> [15,] -0.17444065 1.043356443 -0.49511091 -0.72391258 0.0298645
Running ‘censRegTest.R’ [210s/210s]
Comparing ‘censRegTest.Rout’ to ‘censRegTest.Rout.save’ ...32c32
< -3.942181e-12 -1.212172e-10 -2.733505e-11 -1.305487e-11 -1.584425e-11
---
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---
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- checking for unstated dependencies in vignettes ... OK
- checking package vignettes in ‘inst/doc’ ... OK
- checking running R code from vignettes ... [50s/51s] OK
- checking re-building of vignette PDFs ... [68s/67s] OK
- checking PDF version of manual ... OK
NOTE: There was 1 note.
See
‘/home/ripley/R/packages/tests32/censReg.Rcheck/00check.log’
for details.